LEADER 05451nam 2200685Ia 450 001 9910783724903321 005 20230617004724.0 010 $a1-281-88084-1 010 $a9786611880842 010 $a981-256-779-8 035 $a(CKB)1000000000247185 035 $a(EBL)244549 035 $a(OCoLC)63196349 035 $a(SSID)ssj0000104616 035 $a(PQKBManifestationID)11117014 035 $a(PQKBTitleCode)TC0000104616 035 $a(PQKBWorkID)10085968 035 $a(PQKB)10774230 035 $a(MiAaPQ)EBC244549 035 $a(WSP)00005712 035 $a(Au-PeEL)EBL244549 035 $a(CaPaEBR)ebr10106579 035 $a(CaONFJC)MIL188084 035 $a(OCoLC)935228926 035 $a(EXLCZ)991000000000247185 100 $a20050316d2004 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aApplications of multi-objective evolutionary algorithms$b[electronic resource] /$feditors, Carlos A. Coello Coello, Gary B. Lamont 210 $aSingapore ;$aHackensack, NJ $cWorld Scientific$dc2004 215 $a1 online resource (XXVII, 761 p.) 225 1 $aAdvances in natural computation ;$vv. 1 300 $aDescription based upon print version of record. 311 $a981-256-106-4 320 $aIncludes bibliographical references and index. 327 $aFOREWORD; PREFACE; CONTENTS; CHAPTER 1 AN INTRODUCTION TO MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS AND THEIR APPLICATIONS; CHAPTER 2 APPLICATIONS OF MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS IN ENGINEERING DESIGN; CHAPTER 3 OPTIMAL DESIGN OF INDUSTRIAL ELECTROMAGNETIC DEVICES: A MULTIOBJECTIVE EVOLUTIONARY APPROACH; CHAPTER 4 GROUNDWATER MONITORING DESIGN: A CASE STUDY COMBINING EPSILON DOMINANCE ARCHIVING AND AUTOMATIC PARAMETERIZATION...; CHAPTER 5 USING A PARTICLE SWARM OPTIMIZER WITH A MULTI-OBJECTIVE SELECTION SCHEME TO DESIGN COMBINATIONAL LOGIC CIRCUITS 327 $aCHAPTER 6 APPLICATION OF MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS IN AUTONOMOUS VEHICLES NAVIGATIONCHAPTER 7 AUTOMATING CONTROL SYSTEM DESIGN VIA A MULTIOBJECTIVE EVOLUTIONARY ALGORITHM; CHAPTER 8 THE USE OF EVOLUTIONARY ALGORITHMS TO SOLVE PRACTICAL PROBLEMS IN POLYMER EXTRUSION; CHAPTER 9 EVOLUTIONARY MULTI-OBJECTIVE OPTIMIZATION OF TRUSSES; CHAPTER 10 CITY AND REGIONAL PLANNING VIA A MOEA: LESSONS LEARNED; CHAPTER 11 A MULTI-OBJECTIVE EVOLUTIONARY ALGORITHM FOR THE COVERING TOUR PROBLEM; CHAPTER 12 A COMPUTER ENGINEERING BENCHMARK APPLICATION FOR MULTIOBJECTIVE OPTIMIZERS 327 $aCHAPTER 13 MULTIOBJECTIVE AERODYNAMIC DESIGN AND VISUALIZATION OF SUPERSONIC WINGS BY USING ADAPTIVE RANGE MULTIOBJECTIVE...CHAPTER 14 APPLICATIONS OF A MULTI-OBJECTIVE GENETIC ALGORITHM IN CHEMICAL AND ENVIRONMENTAL ENGINEERING; CHAPTER 15 MULTI-OBJECTIVE SPECTROSCOPIC DATA ANALYSIS OF INERTIAL CONFINEMENT FUSION IMPLOSION CORES: PLASMA GRADIENT...; CHAPTER 16 APPLICATION OF MULTIOBJECTIVE EVOLUTIONARY OPTIMIZATION ALGORITHMS IN MEDICINE; CHAPTER 17 ON MACHINE LEARNING WITH MULTIOBJECTIVE GENETIC OPTIMIZATION; CHAPTER 18 GENERALIZED ANALYSIS OF PROMOTERS: A METHOD FOR DNA SEQUENCE DESCRIPTION 327 $aCHAPTER 19 MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS FOR COMPUTER SCIENCE APPLICATIONSCHAPTER 20 DESIGN OF FLUID POWER SYSTEMS USING A MULTI OBJECTIVE GENETIC ALGORITHM; CHAPTER 21 ELIMINATION OF EXCEPTIONAL ELEMENTS IN CELLULAR MANUFACTURING SYSTEMS USING MULTI-OBJECTIVE GENETIC ALGORITHMS; CHAPTER 22 SINGLE-OBJECTIVE AND MULTI-OBJECTIVE EVOLUTIONARY FLOWSHOP SCHEDULING; CHAPTER 23 EVOLUTIONARY OPERATORS BASED ON ELITE SOLUTIONS FOR BI-OBJECTIVE COMBINATORIAL OPTIMIZATION; CHAPTER 24 MULTI-OBJECTIVE RECTANGULAR PACKING PROBLEM 327 $aCHAPTER 25 MULTI-OBJECTIVE ALGORITHMS FOR ATTRIBUTE SELECTION IN DATA MININGCHAPTER 26 FINANCIAL APPLICATIONS OF MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS: RECENT DEVELOPMENTS AND FUTURE RESEARCH...; CHAPTER 27 EVOLUTIONARY MULTI-OBJECTIVE OPTIMIZATION APPROACH TO CONSTRUCTING NEURAL NETWORK ENSEMBLES FOR REGRESSION; CHAPTER 28 OPTIMIZING FORECAST MODEL COMPLEXITY USING MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS; CHAPTER 29 EVEN FLOW SCHEDULING PROBLEMS IN FOREST MANAGEMENT; CHAPTER 30 USING DIVERSITY TO GUIDE THE SEARCH IN MULTI-OBJECTIVE OPTIMIZATION; INDEX 330 $aThis book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good solutions for high-dimensional real-world design applications. The book contains a large collection of MOEA applications from many researchers, and thus provides the practitioner with detailed algorithmic direction to achieve good results in their selected problem domain. 410 0$aAdvances in natural computation ;$vv. 1. 606 $aCombinatorial optimization 606 $aEvolutionary computation 615 0$aCombinatorial optimization. 615 0$aEvolutionary computation. 676 $a519.3 686 $a31.80$2bcl 701 $aCoello Coello$b Carlos A$0854473 701 $aLamont$b Gary B$0854474 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910783724903321 996 $aApplications of multi-objective evolutionary algorithms$93773214 997 $aUNINA